$ show MrNeRF/awesome-3D-gaussian-splatting
This repository is a curated 'awesome list' for 3D Gaussian Splatting (3DGS) research papers, complemented by a static site generator and a YAML editor. The core functional code reads a YAML database of ~500 papers and generates a single-page HTML site with search, filter by year/tag, and paper selection for sharing. It includes a PyQt6 GUI for managing the YAML file, an arXiv integration module to fetch metadata, a PDF thumbnail generator, and a link checker for CI. The frontend uses vanilla CSS and JS with no framework. The codebase is well-organized for its purpose but lacks deep abstraction; the template engine is a thin wrapper around string.Template, and the editor is tightly coupled to the application. The main value is the curated paper list itself rather than the software engineering.
The LLM identified 3 files worth highlighting for reuse:
Isolated module that fetches paper metadata from arXiv by extracting the paper ID from a URL and calling the arXiv API. Handles ID extraction, result parsing, and YAML formatting. Could be extracted as a standalone library for automated paper metadata retrieval.
Concurrent URL checker that sweeps all URLs in the paper database and reports malformed or unreachable links. Uses threaded requests with retry logic and separates bot-blocked responses from true failures. Designed for CI, outputs a markdown report. Reusable for any project needing dead-link detection.
Data model for a research paper using Python dataclasses with validation (year range, required fields). Provides a from_dict constructor and to_dict serializer. Clean, self-contained, and easily portable to any project that needs to represent and validate academic paper metadata.